Scientist, Computational Chemist & MLOps Engineer

The Position: Highly motivated computational scientist to contribute to machine learning–driven drug discovery efforts, focusing on data engineering, statistical modeling, bioinformatics, and scientific software development.

Responsibilities:
- Develop and apply statistical and machine learning models to experimental datasets
- Design, maintain, and optimize scientific databases and data processing pipelines
- Build reproducible computational workflows for bioinformatics and drug discovery
- Analyze high-dimensional biological datasets and communicate findings
- Contribute production-quality Python code and maintain version-controlled scientific software
- Operate effectively in Linux/HPC environments (remote systems and cloud infrastructure)
- Write clear, maintainable, testable scientific code; debug complex issues independently
- Apply statistically rigorous thinking; maintain reproducibility and software engineering discipline
- Partner with scientists across biology, chemistry, bioinformatics, and computational research
- Support internal computational platform and modeling infrastructure development
- Document workflows/analyses/software to reproducible research standards
- Mentor junior team members and contribute to technical best practices (Scientist II/III)

Requirements:
Scientist I
- BS/MS in Bioinformatics, Biostatistics, Computational Biology, Computer Science, Data Science, Applied Mathematics, or related field
- Strong Python programming; Linux command-line experience
- Foundational statistics and ML knowledge
- Experience with structured/unstructured biological datasets
- Familiarity with Git
Scientist III (in addition)
- Advanced degree (PhD preferred) or equivalent experience
- Leading computational projects independently; advanced applied statistics/predictive modeling/expt interpretation
- Mentoring/leading technical initiatives
- Ability to translate ambiguous problems into robust computational solutions

Preferred:
- Predictive modeling/deep learning; modern ML tooling and evaluation
- Therapeutic design, RNA biology, genomics, or lab experience; sequence-based analysis
- Large-scale biological/omics datasets; distributed computing
- Collaborative software development environment

Benefits:
- Competitive salaries and an excellent benefit package.

Application/Work authorization:
- Candidates must have current, valid authorization to work in the country where the role is located.